Witricity Corporation

Waymo LLC

Alexander Patrick McCauley

Morris P Kesler

Andre B Kurs

Simon Verghese

Volkan Efe

Katherine L Hall

Aristeidis Karalis

Konrad J Kulikowski

Arunanshu Mohan Roy

Pierre-yves Droz

David Neil Hutchison

Luke Wachter

Noam Katz

Maria Empar Rollano Hijarrubia

Andrew J Campanella

Ralph Hamilton Shepard

Eric R Giler

Qiang Li

Brandyn White

Steven J Ganem

Gozde Guckaya

Hiroshi A Mendoza

Marin Soljacic

Dragomir Dimitrov Anguelov

Herbert Toby Lou

Nathan Andrew Pallo

Kylee Devro Sealy

Christopher Buenrostro

Jiyang Gao

Pei Sun

Benjamin Sapp

Hang Zhao

Xin Huang

Matthew J MacDonald

Michael F Lamenza

Xi Xiang Yeng

Kyriacos Christoforos Shiarlis

Abdel Sam Rhoufiry

Simone Agha

An example method includes receiving, from one or more sensors associated with an autonomous vehicle, sensor data associated with a target object in an environment of the vehicle during a first environmental condition, where at least one sensor of the sensor(s) is configurable to be associated with one of a plurality of operating field of view volumes. The method also includes based on the sensor data, determining at least one parameter associated with the target object. The method also includes determining a degradation in the parameter(s) between the sensor data and past sensor data, where the past sensor data is associated with the target object in the environment during a second environmental condition different from the first and, based on the degradation, adjusting the operating field of view volume of the at least one sensor to a different one of the operating field of view volumes.

Adjusting vehicle sensor field of view volume

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for agent trajectory prediction using temporal-spatial interaction predictions.

Multi-modal multi-agent trajectory prediction

The disclosure features wireless energy transfer sources that include at least two source resonators and a power source, where: each of the at least two source resonators has a nominal impedance when a device resonator is not positioned on or near any of the at least two source resonators, the nominal impedances of each of the at least two source resonators varying by 10% or less from one another; and the at least two source resonators are configured so that during operation of the wireless energy transfer source, when a device resonator is positioned on or near a first one of the at least two source resonators: (a) the impedance of the first source resonator is reduced to a value smaller than the nominal impedances of each of the other resonators by a factor of 2 or more.

Wireless power transfer systems for surfaces

The present disclosure relates to systems and methods that utilize machine learning techniques to improve object classification in thermal imaging systems. In an example embodiment, a method is provided. The method includes receiving, at a computing device, one or more infrared images of an environment. The method additionally includes, applying, using the computing device, a trained machine learning system on the one or more infrared images to determine an identified object type in the environment by at least: determining one or more prior thermal maps associated with the environment; using the one or more prior thermal maps and the one or more infrared images, determining a current thermal map associated with the environment; and determining the identified object type based on the current thermal map. The method also includes providing the identified object type using the computing device.

Thermal imaging for self-driving cars

One example method involves obtaining a plurality of images using a camera located at a given position relative to a light detection and ranging (LIDAR) device. A first image of the plurality may be obtained while a first aperture is interposed between the camera and the LIDAR device. A second image of the plurality may be obtained while a second aperture is interposed between the camera and the LIDAR device. The method also involves determining one or more alignment offsets between a transmitter of the LIDAR device and a receiver of the LIDAR device based on the plurality of images.

LIDAR optics alignment systems and methods

Techniques herein provide wireless energy transfer to audio devices such as headphones, headsets, hearing aids, and the like. Audio devices are integrated with a device resonator. The device resonator may be positioned and oriented to reduce interaction with lossy or sensitive components of the audio device. A repeater resonator and/or a source resonator is integrated into a headrest of a seat or a chair providing continuous power to the headphones while in use. The audio devices may be recharged wirelessly when positioned near source resonators that may be embedded in pads, tables, carrying cases, cups, and the like.

Wirelessly powered audio devices

A wireless energy transfer enabled battery includes a resonator that is positioned asymmetrically in a battery sized enclosure such that when two wirelessly enabled batteries are placed in close proximity the resonators of the two batteries have low coupling.

Wireless energy transfer for rechargeable batteries

The disclosure features power transmitting apparatus for wireless power transfer to a receiver that includes a housing having a form factor that corresponds to a container featuring lateral surfaces, a bottom surface, and an opening opposite the bottom surface, a first coil formed by a continuous path of electrically conductive material and featuring a plurality of non-planar loops that conform to a first pair of opposite lateral surfaces and to the bottom surface, and a second coil formed by a continuous path of electrically conductive material and featuring a plurality of non-planar loops that conform to a second pair of opposite lateral surfaces and to the bottom surface.

Wirelessly charged battery system

A wireless energy transfer system may include a first layer of conductive material that may be positioned proximate to a second layer. The second layer of magnetic material may be positioned proximate to the first layer of conductive material and a third layer. The third layer may be positioned proximate to the second layer and a fourth layer, wherein the third layer may include a first resonator coil, wherein the first resonator coil may be configured to transfer wireless energy to a second resonator coil when the second resonator coil is proximate to the first resonator coil. The fourth layer may be positioned proximate to the third layer, wherein the fourth layer may include a plurality of conductive material.

Wireless energy transfer for mobile device applications

Growing community of inventors

Cambridge, MA, United States of America

Alexander Patrick McCauley